Coring is a non-linear filtering technique traditionally used by television engineers to reduce the perceptibility of noise in the luminance signal. Traditional one dimensional (1-D) coring process is effective under the condition that the prefilter is well matched to the signal, and poorly matched to the noise. This condition is often violated in typical image sequences. As a result, a 1-D coring process has never worked well in practice. A signal decomposition better matched to relevant signal features such as coring methods based on a 2-D spatial decomposition of an image into multiple oriented and frequency bands produces better quality in the processed image. These work better than a 1-D coring process because important signal features tend to be spatially oriented, while typical noise is spatially isotropic. The noise is therefore broadly distributed with low amplitude over a number of oriented channels, while each signal feature tends to show up with higher amplitude in only one or a few channels. In previous coring processes, the shape of the coring function is fixed and is the same for every filter at every point in space.
While these techniques have proven useful for still images, they have not produced similar results for sequences of images which vary in time.